Reinforcement Learning Based Active Attack Detection and Blockchain Technique to Protect the Data from the Passive Attack in the Autonomous Mobile Network-Reference-Cited by-同舟云学术

Reinforcement Learning Based Active Attack Detection and Blockchain Technique to Protect the Data from the Passive Attack in the Autonomous Mobile Network

Published:2023-07-19 Issue:4 Volume:131 Page:2697-2714
ISSN:0929-6212
Container-title:Wireless Personal Communications
language:en
Short-container-title:Wireless Pers Commun

Author:

Sivasankar C.,Kumanan T.

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Science Applications

Link

https://link.springer.com/content/pdf/10.1007/s11277-023-10576-0.pdf

Reference27 articles.

1. Mohanty, P. K., & Parhi, D. R. (2014). Navigation of autonomous mobile robot using adaptive network based fuzzy inference system. Journal of Mechanical Science and Technology, 28(7), 2861–2868.

2. Yu, W., & Liu, K. R. (2007). Game theoretic analysis of cooperation stimulation and security in autonomous mobile ad hoc networks. IEEE Transactions on Mobile Computing, 6(5), 507–521.

3. Schilling, F., Chen, X., Folkesson, J., & Jensfelt, P. (2017, September). Geometric and visual terrain classification for autonomous mobile navigation. In 2017 IEEE/RSJ International conference on intelligent robots and systems (IROS) (pp. 2678–2684). IEEE.

4. Tang, Q., Jin, G., Wang, G., Liu, T., Liu, X., Wang, B., & Cao, H. (2020). Current sampling methods for gut microbiota: A call for more precise devices. Frontiers in Cellular and Infection Microbiology, 10, 151.

5. Thing, V. L. (2017, March). IEEE 802.11 network anomaly detection and attack classification: A deep learning approach. In 2017 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1–6). IEEE.